Although smoking results in lung pathology in many, still not all smokers develop chronic obstructive pulmonary disease (COPD). Roughly a quarter of patients with COPD have never smoked. An understanding of both host and environmental factors beyond smoking that contribute to disease development remain critical to understanding disease prevention and ultimately effectively intervene. In this article, we summarize host factors, including genetics and gender, as well as early-life events that contribute to the development of COPD.Chronic obstructive pulmonary disease (COPD) affects about 300 million people worldwide, resulting in approximately 64 million disability-adjusted life years. Household air pollution affects almost 3 billion people worldwide and is a major risk factor for COPD. An estimated 25% to 45% of patients with COPD worldwide have never smoked. Fourteen percent of the overall COPD burden is attributable to occupational exposures. Rural populations are at higher risk for COPD than urban residents. African American never-smokers have a disproportionately high prevalence and Hispanic people have a low prevalence of COPD.Chronic obstructive pulmonary disease (COPD) has been traditionally considered a self-inflicted disease caused by tobacco smoking. Current available evidence, however, indicates that the pathogenesis of COPD needs to consider the dynamic and cumulative nature of a series of environment (including smoking plus other exposures)-host interactions that eventually determine lung development, maintenance, repair, and aging. By doing so, these factors modulate the trajectory of lung function of the individual through life and the odds of developing COPD through different routes, which likely represent different forms of the disease that require different preventive and therapeutic strategies.Human skin acts as a barrier to protect our bodies from UV rays and external pathogens and to prevent water loss. Phenotypes of aging, or natural aging due to chronic damage, include wrinkles and the reduction of skin thickness that occur because of a loss of skin cell function. The dysregulation of autophagy, a lysosome-related degradation pathway, can lead to cell senescence, cancer, and various human diseases due to abnormal cellular homeostasis. Here, we discuss the roles and molecular mechanisms of autophagy involved in the anti-aging effects of autophagy and the relationship between autophagy and aging in skin cells.Cutaneous dysbiosis is implicated in hidradenitis suppurativa (HS) pathogenesis. Previous studies reveal skin microbiota shifts in HS lesional skin. In their report, Riverain-Gillet et al. (2020) extended these findings and reported skin microbiota shifts in unaffected HS skinfolds as well. Their study suggests that skin microbial shifts may precede clinical lesions and draws attention to study methods important for skin microbiome research.Latent class analysis (LCA) is a statistical technique that allows for identification, in a population characterized by a set of predefined features, of hidden clusters or classes, that is, subgroups that have a given probability of occurrence and are characterized by a specific and predictable combination of the analyzed features. Compared with other methods of so called data segmentation, such as hierarchical clustering, LCA derives clusters using a formal probabilistic approach and can be used in conjunction with multivariate methods to estimate parameters. The optimal number of classes is the one that minimizes the degree of relationship among cases belonging to different classes, and it is decided by relying on methods such as the Bayesian Information Criterion that capitalize on the value of the negative log-likelihood function, a well-established measure of the goodness of fit of a statistical model. LCA has not been extensively used in dermatology. The areas of application are manifold, from the phenotype classification to the analysis of behavior in relation with risk factors to the performance of diagnostic tests.To better understand and interpret the trends in cutaneous research, we carried out a network analysis of all the titles of the submitted abstracts of the annual meetings of the European Society of Dermatological Research (ESDR), including the International Investigative Dermatology (IID) meetings between 2010 and 2019. Network analysis is a data science tool to process, analyze, and visualize big sets of data. As expected, psoriasis was the frontrunner in each of the annual meetings, followed by dermatitis and melanoma. Interestingly, alopecia, acne, squamous cell carcinoma, pruritus, basal cell carcinoma, and hidradenitis suppurativa were among the next most frequently named diseases and/or terms. We also looked at diversity to assess how broad the interest of the submitting community is and to identify whether "blockbusters" such as psoriasis and atopic dermatitis expand in expense of other interests. https://www.selleckchem.com/products/relacorilant.html In contrast to our expectations, the diversity of submissions to the ESDR annual meetings remained high over the 10 years of our observation period. Interestingly, the diversity increased in the years of the IID, indicating an outreach to other research areas worldwide compared with the ESDR meetings. This is true for both 2013 in Edinburgh, UK, and 2018 in Orlando, USA. During these meetings, this rise in diversity was associated with a relative decrease of the three most often named diseases. Network analysis thus may be a useful tool for research societies like the ESDR to identify trends and allocate resources such as reviewers and sessions accordingly. In addition, it can serve as quality control monitoring whether the ESDR continues to offer a platform for all researchers in cutaneous biology or implements or focuses on emerging fields.Achieving most of the UN Sustainable Development Goals requires a strong focus on addressing the double burden of malnutrition, which includes both diet-related maternal and child health (MCH) and non-communicable diseases (NCDs). Although, the most optimal dietary metric for assessing malnutrition remains unclear. Our aim was to review available global dietary quality metrics (hereafter referred to as dietary metrics) and evidence for their validity to assess MCH and NCD outcomes, both separately and together. A systematic search of PubMed was done to identify meta-analyses or narrative reviews evaluating validity of diet metrics in relation to nutrient adequacy or health outcomes. We identified seven dietary metrics aiming to address MCH and 12 for NCDs, no dietary metrics addressed both together. Four NCD dietary metrics (Mediterranean Diet Score, Alternative Healthy Eating Index, Healthy Eating Index, and Dietary Approaches to Stop Hypertension) had convincing evidence of protective associations with specific NCD outcomes, mainly mortality, cardiovascular disease, type 2 diabetes, and total cancer.